Pipelines have become an indispensable means of transporting industrial fluids such as petroleum-related products. There are now many thousands of miles of pipelines throughout the world, particularly in North America and the Middle East, where oil reserves are plentiful.
These pipelines have become extremely sophisticated and are now capable of carrying multiple fluids along the same line, the fluids having various compositions, depending upon source grade, level of refinement, destination and the like. As such, the pipeline configurations now include complex switching to route the various fluids in accordance with their intended application.
That these fluids are securely contained within a long-distance conduit facilitates efficient delivery, but also complicates identification during transport. Given a substantially consistent flow rate and no maintenance requirements, fluid switching and collection might be straightforward; [n practice, however, inconsistencies in flow, maintenance issues, and even operator error make fluid identification and error-free distribution increasingly difficult, if not impossible, in some cases.
Of the techniques available to ensure proper fluid identification and distribution, most are highly unsatisfactory. Statistical methods, for example, are only exacting if flow rates, maintenance levels and operator error are contained within predictable boundaries. Manual techniques, which involve sampling the fluid and testing it for composition, are time consuming and contribute to the very inconsistencies that make other techniques such as statistical methods prone to inaccuracy.
Clearly there exists a need for a system to ensure efficient, highly predictable identification and distribution of these valuable fluid commodities while, at the same time, eliminating waste and potential errors.